Association between personality traits of dairy cows and their peripubertal heifer offspring
Bibliographic record
Abstract
This study aimed to determine if personality traits identified in dairy cows during the transition phase are correlated with those of their peripubertal heifer calves. At ~24 d before calving and ~24 d after being first introduced to the automated milking system, the personality traits of 23 Holstein cows were assessed using a combined arena test [consisting of exposure to consecutive novel environment (NE), novel object (NO), and novel human (NH) tests]. Personality traits were established by principal component analysis (PCA) of behaviors expressed in these tests. The PCA of cow behaviors during the precalving test revealed 3 factors, or personality traits, interpreted as exploratory, active, and bold. The PCA of cow behaviors during the postcalving test revealed 2 factors, interpreted as active and exploratory. From these cows, 23 female Holstein heifers were produced and enrolled in this study at 7 mo of age. Heifers were personality tested once through a similar combined arena test. The PCA of heifer behaviors during the NO test revealed 3 factors, interpreted as bold, exploratory-active, and social. The PCA of heifer behaviors during the NH test revealed 2 factors, interpreted as exploratory-active and social. All factor scores from each cow and heifer pair were tested for association. An association between cows with higher scores on the factor interpreted as exploratory and heifers with lower scores on the factor interpreted as bold was detected. There were tendencies for cows with higher scores on the factor interpreted as active to be associated with heifers that scored highly on the factors interpreted as exploratory-active and bold. The data suggests that there are some limited associations between personality traits of cows and their heifer offspring; further exploration of these associations may lead to the prediction of heifer personality based on cow personality.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".